Questions tagged [machine-learning]

Theoretical questions about Machine learning, especially Computational Learning Theory, including Algorithmic Learning Theory, PAC learning, and Bayesian Inference

280 questions
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Learning hidden variable distribution

Consider a set of $k$ continuous variables. Each variable $x_k$ is associated with a hidden distribution from which its value is sampled independently of other variables. I am given a set of ...
153 views

Universal approximation theorem of second order

The universal approximation theorem (https://en.wikipedia.org/wiki/Universal_approximation_theorem) informally states that up to several conditions, any function can be approximated by a shallow ...
94 views

What is the name of the category of problems that can only be solved with machine learning? [closed]

Wikipedia defines machine learning as the "field of computer science that gives computers the ability to learn without being explicitly programmed". A common example of a problem which machine ...
61 views

Is there some research about infinitely many-armed bandit with non-stationary assumption?

Is there some research about infinitely many-armed bandit with non-stationary assumption? I have found the paper about infinitely many-armed bandit under stationary (or stochastic) assumption. And I ...
124 views

Can machine learning algorithms be trained to discard nonsense?

Afaik, the problem with many machine learning algorithms is that they will often label nonsense into some categories. What measures can one take to discard nonsense results? Eg. if you have a bot ...
80 views

References for the computational complexity of training neural networks

I'm looking for a good review paper or book chapter that offers an accessible introduction to the computational complexity of training neural networks for classification problems. In particular, I'm ...
648 views

Can neural networks be used to devise algorithms?

After the newer and newer successes of neural networks in playing board games, one feels that the next goal we set could be something more useful than beating humans in Starcraft. More precisely, I ...
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The dependence of learning generalization bounds on the dimension of the instance space

Here is a popular generalization bound: If $X$ is the input space and $Y=\{0, 1\}$ is the output/label space, and there is a joint distribution $D$ defined on this space. We sample $m$ ...
67 views

Impossibility result on metric learning?

Are there any fundamental limitations (impossibility results) known for metric learning? Are there any direct connection reduction from/to that I can use results in clustering? (e.g. this: 2 ) 2 ...
In the experts problem, $n$ experts give you binary predictions on a daily basis, and you have to predict whether it's going to rain tomorrow. That is, at day $t$, you know the past predictions of ...